Engraphis

Give your AI agents a memory. See it, search it, and watch it self-maintain — all in a beautiful WebUI on your own machine.

Screenshots coming soon — run engraphis-dashboard to see it live.
^{Dashboard · Inspector · Knowledge Graph · Timeline · Recall · Analytics}

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The WebUI — one command, local-first

pip install "engraphis[server]"
engraphis-dashboard

Opens http://127.0.0.1:8700 in your browser. No cloud, no signup, no API key for memory. Everything lives in a single SQLite file on your machine.

You'll see the full product — a dark-themed, sidebar-navigated dashboard with 11 tabs:

Tab	What you see
Overview	Live memory counts, retention distribution, weekly growth, decay forecast, resolver action mix, most-connected entities
Memories	Browse every memory by workspace, sorted by retention — click into a full reader with retention/stability pills
Recall	Search across the entire memory bank — each result shows its score breakdown (retention, semantic, lexical, graph, importance, recency)
Knowledge Graph	Interactive D3 force-directed graph of entities and their relationships — click any node to see every linked memory
Timeline	Chronological feed of every memory event — creation, invalidation, correction, consolidation
Consolidate	Run a consolidation sweep on demand — see what got distilled and what got pruned
Audit	Full governance ledger — who did what, when, and why
Settings	Database stats, license activation (Pro/Team), and system health
Chat	Ask questions against your memory — the LLM answers grounded in context
Vaults	Manage workspace vaults — create, rename, delete, bulk import
Import	Drag & drop or paste markdown files to populate your knowledge base

The dashboard is powered by the v2 engine — the same MemoryService that backs the MCP server and the Python library. What you see in the UI is what your agents get.

Start it on every platform

Platform	How
Windows	Double-click Engraphis Dashboard on your Desktop or Start Menu (install: engraphis-dashboard --install-shortcuts)
macOS	Double-click Engraphis Dashboard.app on your Desktop (install: same command)
Linux	Desktop entry in Applications → Development (GNOME/KDE/etc.)
Any	engraphis-dashboard in a terminal

Also ships with the Memory Inspector

For a focused, accessibility-first view of individual memories and their history:

engraphis-inspector

Opens http://127.0.0.1:8710 with:

• Search by query with score breakdown
• Supersession-chain view with word-level diffs — see exactly when a fact changed and why
• Why/timeline/link browsing, proactive recall, consolidation, audit trail
• Keyboard-navigable, ARIA-annotated, light/dark mode via prefers-color-scheme

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What's under the UI

Your agents forget everything between sessions. Engraphis fixes that — on your machine. Every new session, your coding agent starts from zero: re-asking which package manager you use, re-learning the codebase, forgetting why you chose PASETO over JWT. Engraphis gives agents durable, scoped, explainable memory.

Under the hood: Ebbinghaus forgetting-curve decay, interaction-aware reinforcement, bi-temporal facts, and hybrid (vector + lexical + graph) recall. The engine is 100% local: SQLite + local embeddings. You bring the LLM only for optional chat/synthesis.

• Local-first & private — runs offline; the core depends only on numpy.
• MCP-native — 18 tools for Claude Code, Cursor, Cline, Zed, Windsurf.
• Self-maintaining facts — writes are deterministically conflict-resolved (no LLM required).
• Principled recall — six-term score over retention, semantic, lexical, graph, importance, recency.
• Bi-temporal truth — contradictions invalidate instead of overwriting (engraphis_why / engraphis_timeline).
• Grounded, not guessed — cited answers or explicit abstain; provenance on every memory.
• Code-aware — AST-powered symbol graph: engraphis_index_repo → engraphis_search_code.
• Sleep-time consolidation — scheduled job distills recurring episodes, reports its compaction.
• Scoped — workspace → repo → session hierarchy.

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Why it wins

Axis	Neocortex	mem0	Zep	Engraphis
Product WebUI (local, no cloud)	✗	✗	✗	✓ (dashboard + Inspector)
Open & self-hostable engine	✗	✓	partial	✓ fully open, local-first
Forgetting/decay	✓	partial	✗	✓
Bi-temporal graph	✗	partial	✓	✓
Native multi-repo model	✗	✗	✗	✓ (unique)
Code-aware (AST/symbol graph)	✗	✗	✗	✓ (unique)
MCP-native for coding agents	✗	✓	✗	✓

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Install

pip install "engraphis[all]"    # dashboard + MCP server + code graph + everything
pip install "engraphis[server]" # dashboard + REST API
pip install "engraphis[mcp]"    # MCP server only
pip install engraphis           # core library — numpy only, fully offline

First run downloads all-MiniLM-L6-v2 (~80 MB). Without it, the engine falls back to a deterministic offline embedder so it always runs.

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Quickstart — dashboard (the headline)

pip install "engraphis[server]"
engraphis-dashboard                   # → http://127.0.0.1:8700
engraphis-dashboard --install-shortcuts   # → Desktop + Start Menu icons

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Quickstart — MCP server (for coding agents)

pip install "engraphis[mcp]"
engraphis-init                     # writes .env + prints config snippets
claude mcp add engraphis -- engraphis-mcp

Your agent now has 18 tools — remember, recall (grounded + proactive), why, timeline, forget, pin, correct, ingest, consolidate, index_repo, search_code, link, record_event, start/end_session, stats. See the MCP tools table below.

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Quickstart — Python library

from engraphis.service import MemoryService

mem = MemoryService.create("engraphis.db")
mem.remember("Auth migrated from JWT to PASETO.", workspace="acme", repo="api")
hit = mem.recall("why did we change auth?", workspace="acme", repo="api")
print(hit["context"])

The same MemoryService backs the dashboard, the Inspector, and the MCP server.

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Free forever vs. Pro

The engine, dashboard, Inspector, MCP server, and governance tools are free and Apache-2.0, permanently. A license key (verified offline — no phone-home) unlocks the paid layer.

⚠️ Pro and Team are coming soon — not available for purchase yet. Features below are built and gated but keys are not sold today. Do not pay anyone for an Engraphis license right now. Prices are targets, not live.

	Free (available now)	Pro — coming soon	Team — coming soon
Dashboard WebUI + Inspector	✓	✓	✓
Memory engine + 18 MCP tools	✓	✓	✓
Analytics dashboard (growth, retention, decay forecast)		✓	✓
Compliance export (full bi-temporal JSON dump)		✓	✓
Multi-user Inspector: logins, roles, seat management			✓
Analytics HTML report export (self-contained, shareable)			✓
Priority support		✓	✓

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MCP tools

Category	Tool	What it does
Write	engraphis_remember	Store a fact; deterministically resolved (add/reinforce/supersede)
Write	engraphis_record_event	Append a lightweight episodic log entry
Write	engraphis_link	Explicitly connect two related memories
Read	engraphis_recall	Hybrid vector + lexical + graph recall
Read	engraphis_recall_grounded	Cited answer from retrieved memories — or abstain
Read	engraphis_recall_proactive	"What should I know right now" — no query needed
Read	engraphis_why	Current answer + what it superseded
Read	engraphis_timeline	Full bi-temporal history, oldest first
Code	engraphis_index_repo	Parse a repo into the code symbol graph
Code	engraphis_search_code	Find symbols by name, with callers
Governance	engraphis_forget	Retire a memory — bi-temporal close, never deleted
Governance	engraphis_pin	Exempt from future automatic decay/pruning
Governance	engraphis_correct	Replace content without losing history
Session	engraphis_start_session / engraphis_end_session	Session lifecycle with cross-session handoff
Ops	engraphis_stats	Memory counts for health checks

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Configuration

All via environment (or .env):

Env Var	Default	Description
ENGRAPHIS_DB_PATH	./engraphis.db	SQLite database file
ENGRAPHIS_HOST	127.0.0.1	Server bind address
ENGRAPHIS_PORT	8700	Dashboard port
ENGRAPHIS_API_TOKEN	—	If set, REST API requires Authorization: Bearer <token>
ENGRAPHIS_EMBED_MODEL	all-MiniLM-L6-v2	sentence-transformers model
ENGRAPHIS_LLM_PROVIDER	openai	openai | anthropic | google | openrouter
ENGRAPHIS_LLM_API_KEY	—	LLM API key (only for chat/synthesis)
ENGRAPHIS_LICENSE_KEY	—	Pro/Team key (or ~/.engraphis/license.key)

See .env.example for the full list.

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Project structure

engraphis/
├── engraphis/
│   ├── core/                # v2 engine — interfaces, store, recall, scoring, schema
│   ├── backends/            # pluggable embedder / vector index / reranker / codegraph
│   ├── service.py           # validated MemoryService facade
│   ├── mcp_server.py        # MCP server — 18 tools
│   ├── dashboard_app.py     # dashboard WebUI (FastAPI)
│   ├── config.py / app.py   # env settings / REST server
│   └── static/              # dashboard frontend
├── eval/                    # offline retrieval eval harness + datasets
├── tests/                   # pytest suite (offline, numpy-only core)
├── scripts/                 # start_dashboard, inspector, cli, init, consolidate
├── Dockerfile / docker-compose.yml
└── pyproject.toml

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Development

The offline quality gate (no network, no API key):

pip install numpy pytest ruff
python -m pytest tests/ -q
python -m eval.harness --dataset eval/datasets/sample.jsonl --k 5
python -m eval.harness --dataset eval/datasets/codemem.jsonl --k 5
python -m eval.ablation
ruff check .

Numbers, not assertions: the offline harness is a correctness floor (deterministic embedder). LoCoMo / LongMemEval competitive numbers run separately with a real embedder — see BENCHMARKS.md.

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License

Apache-2.0 — see LICENSE and NOTICE. "Engraphis" is a trademark of the Engraphis project; the license does not grant trademark rights.